This edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9–12 January 2020 in conjunction with 16t

This work explores probabilistic models of supervised learning problems and addresses the key statistical and computational questions. Chapters survey research

A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machin

An intuitive approach to machine learning covering key concepts, real-world applications, and practical Python coding exercises.

This volume develops an effective theory approach to understanding deep neural networks of practical relevance.